معرفی
Dr. Jiang (Linda) Xie is a Professor in the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte, where she serves as an IEEE Fellow. Her research focuses on wireless and mobile networks with applications in edge computing, mobile augmented reality, and energy-efficient systems. She maintains an active research laboratory with several current PhD students working on cutting-edge networking problems.
Her research interests span wireless networking, mobile computing, edge computing, mobile AR/MR/VR, intelligent and connected vehicles, and energy-efficient system design. Dr. Xie's work addresses fundamental challenges in communications networks, particularly in the areas of mobility management, spectrum utilization, and performance analysis of next-generation wireless systems. Her research group has produced numerous publications in top-tier venues including IEEE Transactions and INFOCOM.
Dr. Xie's research output demonstrates consistent contributions to wireless networking, with recent publications focusing on cognitive radio networks, handoff management in mesh networks, and mobility solutions for emerging wireless architectures. Her work shows progression from foundational network protocols to more complex systems addressing contemporary challenges in mobile computing and edge infrastructure.
- IEEE Fellow
Dr. Xie has successfully mentored numerous PhD and Master's students, many of whom have secured faculty positions at universities or engineering roles at major technology companies including Google, Amazon, Apple, and Qualcomm. Her students have received prestigious awards including NSF CRII Awards, Best Paper Awards at IEEE GLOBECOM, and Graduate Dean's Distinguished Dissertation Awards. She maintains active research collaborations and has supervised students working on projects funded by various research grants.
Her laboratory focuses on wireless network protocols, mobile computing systems, and performance analysis of communications networks, with current projects addressing challenges in spectrum management, edge computing for mobile applications, and energy-efficient network design.
